Service providers and device manufacturers (e.g., wireless, cellular, etc.) are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services. Many of these services rely on accurate location information to operate. For example, location-based services such as mapping and navigation traditionally rely on accurate positioning of consumers. Accurate positioning by satellite-based systems is hindered by a variety of errors, including multipath effects induced by signal reflection from surrounding terrain, tall buildings, trees, or other natural or man-made land formations. To accurately match consumers to roads (i.e., map matching), these systems attempt to reposition the inaccurate probe data from a positioning device back to the correct road by assuming a uniform positioning error for the entire system and a constant road width, regardless of lane counts or the actual physical extent of roads in the network. Probe data that does not fall within the assigned road width is considered untrustworthy and is discarded. As such, existing map matching techniques fail to correctly match probe data at points where the probe data is usually inaccurate because they are unable to take local error conditions into account.